The influence of the type of contraction on the masseter muscle EMG power spectrum

Different behaviours of the EMG power spectrum across increasing force levels have been reported for the masseter muscle. A factor that could explain these different behaviours may be the type of contraction used, as was recently shown for certain upper limb muscles⁵. The purpose of this study was to compare, between two types of isometric contractions, the behaviour of EMG power spectrum statistics (median frequency (MF) and mean power frequency (MPF)) obtained across increasing force levels. Ten women exerted, while biting in the intercuspal position, three 5 s ramp contractions that increased linearly from 0 to 100% of the maximal voluntary contraction (MVC). They also completed three step contractions (constant EMG amplitude) at each of the following levels: 20, 40, 60 and 80% MVC. EMG signals from the masseter muscle were recorded with miniature surface electrodes. The RMS, as well as the MPF and MF of the power spectrum were calculated at 20, 40, 60 and 80% MVC for each type of contraction. As expected, the RMS values showed similar increases with increasing levels of effort for both types of contractions. Different behaviours for both MPF (contraction^*force interaction, ANOVA, P<0.05) and MF (contraction^*force interaction, ANOVA, P>0.05) across increasing levels of effort were found between the two types of contraction. The use of step contractions gave rise to a decrease of both MPF and MF with increasing force, while the use of ramp contractions gave rise to an increase in both statistics up to at least 40% MVC followed by a decrease at higher force levels. These findings suggest that the type of contraction used does influence the behaviour of the spectral statistics across increasing force levels and that this could explain the differences obtained in previous studies for the masseter muscle.     

Diol sulfonamides: A potent and novel class of inhibitors of human renin

The syntheses and pharmacological activity of a series of diol sulfonamides which function as inhibitors of human renin are described. The most potent compound in this series, compound 20 (SQ 33,800), is a subnanomolar inhibitor of human renin (IC₅₀ = 0.35 × 10⁻⁹ M).     

Smart hydrogels based on semi-interpenetrating polymeric networks of collagen-polyurethane-alginate for soft/hard tissue healing,drug delivery devices,and anticancer therapies

In this work, hydrogels based on semi-interpenetrating polymeric networks (semi-IPN) based on collagen-polyurethane-alginate were studied physicochemically and from different approaches for biomedical application. It was determined that the matrices in the hydrogel state are crosslinked by the formation of urea and amide bonds between the biopolymer chains and the polyurethane crosslinker. The increment in alginate content (0–40 wt%) significantly increases the swelling capacity, generating semi-crystalline granular structures with improved storage modulus and resistance to thermal, hydrolytic, and proteolytic degradation. The in vitro bioactivity results indicated that the composition of these novel hydrogels stimulates the metabolic activity of monocytes and fibroblasts, benefiting their proliferation; while in cancer cell lines, it was determined that the composition of these biomaterials decreases the metabolic activity of breast cancer cells after 48 h of stimulation, and for colon cancer cells their metabolic activity decreases after 72 h of contact for the hydrogel with 40 wt% alginate. The matrices show a behavior of multidose release of ketorolac, and a higher concentration of analgesic is released in the semi-IPN matrix. The inhibition capacity of Escherichia coli is higher if the polysaccharide concentration is low (10 wt%). The in vitro wound closure test (scratch test) results indicate that the hydrogel with 20 wt% alginate shows an improvement in wound closure at 15 days of contact. Finally, the bioactivity of mineralization was evaluated to demonstrate that these hydrogels can induce the formation of carbonated apatite on their surface. The engineered hydrogels show biomedical multifunctionality and they could be applied in soft and hard tissue healing strategies, anticancer therapies, and drug release devices.     

Forest resistance to drought in a humid tropical dipterocarp forest in the Western Ghats of India

Droughts are linked to tree die-offs in the biodiverse humid tropics. We assessed drought response of a Dipterocarp Forest and found a marginal decrease in tree survival, indicating drought resistance. Understory and emergent species were sensitive to drought. Urgent focus is needed to understand drought impacts and plant physiological responses in South Asian forests.     

Bayesian estimation of two-part joint models for a longitudinal semicontinuous biomarker and a terminal event with INLA: Interests for cancer clinical trial evaluation

Two-part joint models for a longitudinal semicontinuous biomarker and a terminal event have been recently introduced based on frequentist estimation. The biomarker distribution is decomposed into a probability of positive value and the expected value among positive values. Shared random effects can represent the association structure between the biomarker and the terminal event. The computational burden increases compared to standard joint models with a single regression model for the biomarker. In this context, the frequentist estimation implemented in the R package frailtypack can be challenging for complex models (i.e., a large number of parameters and dimension of the random effects). As an alternative, we propose a Bayesian estimation of two-part joint models based on the Integrated Nested Laplace Approximation (INLA) algorithm to alleviate the computational burden and fit more complex models. Our simulation studies confirm that INLA provides accurate approximation of posterior estimates and to reduced computation time and variability of estimates compared to frailtypack in the situations considered. We contrast the Bayesian and frequentist approaches in the analysis of two randomized cancer clinical trials (GERCOR and PRIME studies), where INLA has a reduced variability for the association between the biomarker and the risk of event. Moreover, the Bayesian approach was able to characterize subgroups of patients associated with different responses to treatment in the PRIME study. Our study suggests that the Bayesian approach using the INLA algorithm enables to fit complex joint models that might be of interest in a wide range of clinical applications.     

Contribution of the different planktonic microbial assemblages to ETS activity in the Ligurian frontal area: north-west Mediterranean Sea

Spatial and size distribution of micro-organisms and their ETSactivity has been investigated in Ligurian Sea surface watersalong the Nice-Calvi transect across frontal areas from 18 to37 km offshore (TOMOFRONT 1 and 2 cruises, April 1988 and April-May1989 respectively). Aplastidic and plastidic nanoflagellatesand aplastidic picoflagellates were present in numbers closeto 0.25 x 10⁴ cells ml^–1, whereas plastidic picoflagellatesaccounted for about half this number. Correlations have beenevidenced between plastidic and aplastidic micro-organisms withinthe same size group, suggesting that they belong to a well-definedecosystem. The highest correlation between total ETS activityand abundance of the considered size groups was observed fornanoflagellates (r = 0.94, n = 22, and r = 0.90, n = 22 foraplastidic and plastidic cells respectively). The importanceof the role of nanoflagellates in surface waters, with respectto the overall ETS activity, was supported by results from sizefractionation which assigned to the 3–10 µm sizerange a 73.3% contribution to overall ETS activity. Resultsemphasize analysing global ETS activity of natural samples inorder to derive relationships between the different populationspresent in the sampled water. It is suggested that couplingflow cytometry to the ETS approach should be very helpful inthat respect.     

A Quantitative Technique to Compare and Classify Humpback Whale (Megaptera novaeangliae) Sounds

In an attempt to minimize observer bias, numerical taxonomy methods were used to describe and classify humpback whale sounds. The spectrograms (N = 1255) were digitized into a 16 × 21 binary matrix. The rows were 16 frequencies selected on a logarithmic scale (0.12–8 kHz). The columns were 21 time samples taken every 0.1 s. Each point of the matrix was coded 1 if it lay over part of the sound. Other binary variables were added to code for relative intensity within a sound, frequency modulation and amplitude modulation. The sounds were then compared using the Jaccard similarity coefficient for binary data, and classified with average linkage cluster analysis. This technique produced 115 clusters, which were compared with my aural and visual impressions of the sounds. I agreed with most major categories identified by cluster analysis, but many small clusters had to be fused to other categories. This was partially due to the technique used, and to the complexity of the repertoire under study. Improvements are proposed to further reduce observer bias in classification of sounds, and thus make studies of animal communication performed by different researchers or on different species more easily comparable.